Table of Contents
Signal filtering is a fundamental process in biomedical instrumentation. It helps in removing noise and unwanted signals from physiological data, ensuring accurate measurements. Different filtering techniques are used depending on the specific application and signal characteristics.
Types of Signal Filters
Common types of filters include low-pass, high-pass, band-pass, and band-stop filters. Each serves a specific purpose in isolating desired signal components or eliminating interference.
Practical Applications
In electrocardiography (ECG), filters remove baseline wander and high-frequency noise to clarify heart signals. In electromyography (EMG), filtering enhances muscle activity signals by reducing artifacts. These techniques improve diagnostic accuracy and data reliability.
Filtering Techniques
Digital filtering methods, such as finite impulse response (FIR) and infinite impulse response (IIR), are widely used. They offer precise control over frequency response and are implemented in software or hardware systems.
- FIR filters
- IIR filters
- Notch filters
- Kalman filters